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Lagrangian observations of homogeneous random environments

Published online by Cambridge University Press:  01 July 2016

Craig L. Zirbel*
Affiliation:
Bowling Green State University
*
Postal address: Department of Mathematics and Statistics, Bowling Green State University, Bowling Green, OH 43403-0221, USA. Email address: zirbel@bgnet.bgsu.edu

Abstract

This article deals with the distribution of the view of a random environment as seen by an observer whose location at each moment is determined by the environment. The main application is in statistical fluid mechanics, where the environment consists of a random velocity field and the observer is a particle moving in the velocity field, possibly subject to molecular diffusion. Several results on such Lagrangian observations of the environment have appeared in the literature, beginning with the 1957 dissertation of J. L. Lumley. This article unites these results into a simple unified framework and rounds out the theory with new results in several directions. When the environment is homogeneous, the problem can be re-cast in terms of certain random mappings on the physical space that are based on the random location of the observer. If these mappings preserve the invariant measure on the physical space, then the view from the random location has the same distribution as the view from the origin. If these mappings satisfy the flow property and the environment is stationary, then the succession of Lagrangian observations over time forms a strictly stationary process. In particular, for motion in a homogeneous, stationary, and nondivergent velocity field, the Lagrangian velocity (the velocity of the particle) is strictly stationary, which was first observed by Lumley. In the compressible case, the distribution of a Lagrangian observation has a density with respect to the distribution of the view from the origin, and in some cases convergence in distribution of the Lagrangian observations as time tends to infinity can be shown.

Type
General Applied Probability
Copyright
Copyright © Applied Probability Trust 2001 

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References

Bennett, C. D. and Zirbel, C. L. (2000). Discrete velocity fields with known Lagrangian law. Submitted. Available at http://www-math.bgsu.edu/simzirbel/papers/.Google Scholar
Bhattacharya, R. (1985). A central limit theorem for diffusions with periodic coefficients. Ann. Prob. 13, 385396.Google Scholar
Çaglar, M., (1997). Flows generated by velocity fields of Poisson shot-noise type: Lyapunov exponents. , Princeton University.Google Scholar
Carmona, R. A. and Xu, L. (1997). Homogenization for time-dependent two-dimensional incompressible Gaussian flows. Ann. Appl. Prob. 7, 265279.Google Scholar
Davis, R. E. (1982). On relating Eulerian and Lagrangian velocity statistics: single particles in homogeneous flows. J. Fluid Mech. 114, 126.Google Scholar
Fannjiang, A. and.Google Scholar
Komorowski, T. (1999). Turbulent diffusion in Markovian flows. Ann. Appl. Prob. 9, 591610.Google Scholar
Federer, H. (1969). Geometric Measure Theory. Springer, New York.Google Scholar
Geman, D. and.Google Scholar
Horowitz, J. (1975). Random shifts which preserve measure. Proc. Amer. Math. Soc. 49, 143150.Google Scholar
Harris, T. E. (1981). Brownian motions on the homeomorphisms of the plane. Ann. Prob. 9, 232254.Google Scholar
Komorowski, T. and Papanicolaou, G. C. (1997). Motion in a Gaussian incompressible flow. Ann. Appl. Prob. 7, 229264.Google Scholar
Kunita, H. (1990). Stochastic Flows and Stochastic Differential Equations. Cambridge University Press.Google Scholar
Lee, W. C. (1974). Random stirring of the real line. Ann. Prob. 2, 580592.Google Scholar
Lumley, J. L. (1957). Some problems connected with the motion of small particles in turbulent fluid. , The Johns Hopkins University, Baltimore, MD.Google Scholar
Lumley, J. L. (1962). The mathematical nature of the problem of relating Lagrangian and Eulerian statistical functions in turbulence. In Mécanique de la Turbulence (Coll. Internat. CNRS, Marseille, 1961), CNRS, Paris, pp. 1726.Google Scholar
Lyons, R. and Schramm, O. (1999). Stationary measures for random walks in a random environment with random scenery. New York J. Math. 5, 107113.Google Scholar
Matsumoto, H. and Shigekawa, I. (1985). Limit theorems for stochastic flows of diffeomorphisms of jump type. Z. Wahrscheinlichkeitsth. 69, 507540.Google Scholar
Mecke, J. (1975). Invarianzeigenschaften allgemeiner Palmscher Maße. Math. Nachr. 65, 335344.Google Scholar
Middleton, J. F. and Garrett, C. (1986). A kinematic analysis of polarized eddy fields using drifter data. J. Geophys. Res. 91, 50945102.Google Scholar
Monin, A. S. and Yaglom, A. M. (1971). Statistical Fluid Mechanics: Mechanics of Turbulence. MIT Press, Cambridge, MA.Google Scholar
Osada, H. (1982). Homogenization of diffusion processes with random stationary coefficients. In Proc. 4th Japan–USSR Symp. Prob. Theory (Lecture Notes Math. 1021), Springer, Berlin, pp. 507517.Google Scholar
Papanicolaou, G. C. and Varadhan, S. R. S. (1982). Diffusions with random coefficients. In Statistics and Probability: Essays in Honor of C. R. Rao, eds. Kallianpur, G., Krishnaiah, P. R. and Ghosh, J. K., North-Holland, Amsterdam, pp. 547552.Google Scholar
Port, S. C. and Stone, C. J. (1976). Random measures and their application to motion in an incompressible fluid. J. Appl. Prob. 13, 498506.CrossRefGoogle Scholar
Revuz, D. and Yor, M. (1991). Continuous Martingales and Brownian Motion. Springer, Berlin.Google Scholar
Rudin, W. (1987). Real and Complex Analysis. McGraw-Hill, New York.Google Scholar
Zirbel, C. L. (1993). Stochastic flows: dispersion of a mass distribution and Lagrangian observations of a random field. , Princeton University.Google Scholar
Zirbel, C. L. (1997). Markov motion in a homogeneous random environment. Unpublished manuscript.Google Scholar
Zirbel, C. L. and Çinlar, E., (1997). Mass transport by Brownian flows. In Stochastic Models in Geosystems (IMA Vols Math. Appl. 85), ed. Molchanov, S. A., Springer, New York.Google Scholar